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Physics Condensed Matter

cond-mat Watch Condensed Matter

Monday 23 March

Materials Science · Cross-listed from physics.chem-ph

olLOSC: Unified and efficient density functional approximation to correct delocalization error in molecules and periodic materials

Yichen Fan, Jacob Z. Williams and Weitao Yang

Density functional theory (DFT) is the most promising method for calculating quantum properties of molecules and materials at moderate and large scales. However, commonly used density functional approximations (DFAs) have systematic delocalization error, as demonstrated by underestimated band gaps, over-delocalized charges, and energy level misalignment at interfaces, which limits its quantitative prediction. Extensive efforts, such as the $GW$ approximation to many-body perturbation theory, system-specific tuning of DFA parameters, and correction functionals have been developed to address delocalization error. However, an accurate, efficient, and unified solution to describe total energy, charge density and band structure for both finite systems and materials is still not available. Building on the linear-response localized orbital scaling correction (lrLOSC), we introduce olLOSC: a localized orbital scaling correction with curvature calculated by orbital-free electronic linear response. olLOSC has comparable accuracy to lrLOSC, but is much more computationally efficient. olLOSC corrects delocalization error - especially underestimated gaps, but also the total energy - both in molecules and in materials with small and moderate band gaps, within the same orbital-free approximation. Critically, with a a unified approximation, olLOSC opens the path for robust and efficient DFT applications across molecules, materials, and interfaces.
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Soft Condensed Matter

Emergent single-species non-reciprocity from bistable chemical dynamics

Jakob Metson and Ramin Golestanian

The appearance of emergent symmetries in complex systems with components that can form composite units provides us with opportunities for design and control of exotic phase behaviour, for example by exploiting the dynamical symmetry breaking associated with them. We present a novel mechanism for the emergence of non-reciprocal interactions in a single-species suspension of chemically active colloids made out of semi-permeable vesicles, which encapsulate enzymes that catalyze a non-linear chemical reaction. Bistable chemical dynamics enables the colloidal reaction chamber to act as a net producer or consumer of a chemical, depending on the selected values of the chemical concentrations inside and around it. Since the internal chemical state of the colloid depends on the dynamic chemical concentrations rather than the material parameters, two identically produced colloids can present different effective chemical interactions within the same system upon responding to the corresponding gradients via diffusiophoresis. Furthermore, the colloids can spontaneously and reversibly switch between being effective consumers or producers. As a consequence, the colloids can dynamically switch between ignoring, attracting, repelling, and chasing each other, in a non-reciprocal manner. This flexibility can be exploited by manipulation of tuning parameters to induce bifurcations in the chemical dynamics, resulting in a robust control over the interaction motifs, and rich emergent dynamics such as spontaneous many-body polar swarming.
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Materials Science

A Unified Heterogeneous Implementation of Numerical Atomic Orbitals-Based Real-Time TDDFT within the ABACUS Package

Taoni Bao, Yuanbo Li, Zichao Deng et al. (+6 more)

We present a unified heterogeneous computing framework for real-time time-dependent density functional theory (RT-TDDFT) based on numerical atomic orbitals (NAOs), implemented in the ABACUS package. We introduce three co-designed abstraction layers, including unified data containers, unified linear algebra operators, and unified grid integration interfaces. These layers collectively accelerate the two most demanding parts of NAO-based RT-TDDFT: explicit real-time wavefunction propagation and real-space grid operations such as Hamiltonian construction and force evaluation under external fields. We validate the method by computing optical properties for systems ranging from finite molecules to periodic solids, showing excellent agreement with standard benchmarks. Performance evaluations on bulk silicon demonstrate that a single GPU can achieve substantial wall-clock speedup over a fully utilized dual-socket CPU node. Furthermore, distributed multi-GPU strong-scaling tests confirm high parallel efficiency over tens of GPUs. This work establishes a high-performance, portable platform for large-scale first-principles simulations of ultrafast electron dynamics.
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All authors Taoni Bao, Yuanbo Li, Zichao Deng, Haotian Zhao, Denghui Lu, Yike Huang, Chao Lian, Lixin He, Mohan Chen

Mesoscale and Nanoscale Physics

Invariant ionic conductance in an atomically thin polar nanopore

Shengping Zhang, Haiou Zeng, Ningran Wu et al. (+11 more)

Ion channels regulate many essential properties of biological cells, especially the membrane potential. Despite decades of efforts on artificial channels, it remains a great challenge to mimic the dipole potential-an indispensable constituent of the membrane potential, due to its angstrom-scale characteristic length. Here, we explore nanopores in monolayer molybdenum sulfide selenide (MoSSe) considering its intrinsic dipole and atomic thickness. Remarkably, an invariant ionic conductance was observed over salt concentrations spanning six orders of magnitude, distinct from all known conductance-concentration scaling laws and reminiscent of the current saturation in cell membranes at high concentrations. Molecular dynamics simulations revealed the fundamental role of the dipole-modulated dielectric properties of nanoconfined water. Our findings highlight an exotic conductance scaling law and open up a novel avenue for controlling ion transport in unprecedented ways.
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All authors Shengping Zhang, Haiou Zeng, Ningran Wu, Guodong Xue, Xiao Li, Anshul Saxena, Junhe Tong, Nianjie Liang, Zeyu Zhuang, Jing Yang, Narayana R. Aluru, Kaihui Liu, Bai Song, Luda Wang

Materials Science

Small-Data Machine Learning Uncovers Decoupled Control Mechanisms of Crystallinity and Surface Morphology in $\beta$-Ga2O3 Epitaxy

Min Peng, Yuanjun Tang, Dianmeng Dong et al. (+12 more)

The ultrawide-bandgap semiconductor $\beta$-Ga2O3 holds exceptional promise for next-generation power electronics and deep-ultraviolet optoelectronics, yet its widespread application is hindered by the lack of cost-effective, high-quality heteroepitaxial thin films. Here, we demonstrate an interpretable machine learning framework that efficiently navigates the complex, multiparameter process space of pulsed laser deposition (PLD) to achieve high-crystallinity $\beta$-Ga2O3 epitaxy on c-plane sapphire. By systematically benchmarking nine regression algorithms under limited experimental data conditions, we identify quadratic polynomial ridge regression as the optimal surrogate model, which combines predictive accuracy (R$^2$ $\approx$ 0.86) with full physical transparency through explicit analytical coefficients. Coupling this model with SHAP (SHapley Additive exPlanations) analysis and iterative experimental design, we construct a closed-loop optimization workflow that progressively refines the process-performance landscape over only three experimental rounds. This data-efficient strategy reduces the X-ray rocking curve (RC) full-width at half-maximum (FWHM) by 70$\%$ from > 3$^{\circ}$ to 0.92$^{\circ}$, which is the best reported value for PLD-grown $\beta$-Ga2O3 on sapphire. Intriguingly, concurrent modeling of surface roughness reveals that crystalline quality and surface morphology are governed by distinct dominant factors: temperature primarily controls bulk crystallinity, whereas oxygen pressure dictates surface kinetics. This decoupled mechanism, quantitatively captured for the first time via feature importance analysis, provides actionable physical insight for independent optimization of structural and morphological properties. Our work establishes a generalizable, resource-efficient paradigm for intelligent process development in oxide epitaxy and beyond.
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All authors Min Peng, Yuanjun Tang, Dianmeng Dong, Yang Zhang, Cheng Wang, Shulin Jiao, Xiaotong Ma, Shichao Zhang, Jingchen Wang, Huiying Wang, Yongxin Zhang, Huiping Zhu, Yue-Wen Fang, Fan Zhang, Zhenping Wu

Disordered Systems and Neural Networks

Many-body mobility edges in one dimension revealed by efficient and interpretable feature-based learning with Kolmogorov-Arnold Networks

Siqi Dai, Tian-Cheng Yi, Xingbo Wei et al. (+1 more)

We study the many-body localization (MBL) transition in interacting fermionic systems on disordered one-dimensional lattices using a physics-informed machine-learning framework. Instead of feeding full many-body wave functions into the model, we construct a compact feature representation based on four physically motivated observables: the inverse participation ratio, the Shannon entropy, the many-body hybridization parameter, and the mean level-spacing ratio. These quantities capture complementary aspects of localization, entanglement, and spectral correlations, and are used to train a Kolmogorov–Arnold Network (KAN) classifier on eigenstates deep in the weak and strong disorder regimes. The resulting KAN achieves a validation accuracy exceeding $99.9\%$, comparable to that of convolutional neural networks trained directly on high-dimensional wave-function data, while requiring substantially reduced input dimensionality and significantly shorter training time. Applying the trained classifier across the full energy spectrum yields energy-resolved phase diagrams that reveal a clear many-body mobility edge and provide a consistent estimate of the critical disorder strength. The approach is inherently extensible: additional physically relevant observables can be incorporated into the feature space in a systematic manner without altering the overall architecture. Our results demonstrate that feature-based learning with KAN provides an efficient, scalable, and interpretable methodology for identifying many-body localization transitions, offering a practical alternative to raw-data-based neural network approaches.
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All authors Siqi Dai, Tian-Cheng Yi, Xingbo Wei, Yunbo Zhang

Strongly Correlated Electrons

Hall viscosity and putative quantum Hall states without positive-definite K-matrix

Emanuele Di Salvo, Dirk Schuricht, Joost K. Slingerland et al. (+1 more)

We investigate putative quantum Hall effect states, labeled by their K-matrix equal to (1 1 3), by defining them on the torus and computing their Hall viscosity. Such states have been introduced on the sphere as a phase distinct from Pfaffian and anti-Pfaffian ones. This was done in order to explain certain results on thermal Hall conductivity in favor of particle-hole symmetric Pfaffian topological order in presence of Landau level mixing. The requirements of boundary conditions, modular invariance and ground state degeneracy are enough to uniquely fix the form of the proposed wave functions. We generalize a method to enforce them which we call monodromy matching and check our results on wave functions and Hall viscosity against realizations on the torus of Laughlin and hierarchical states. We highlight the issues in the realization of these states, which turn out to exhibit the formation of clusters. We show that the effect of anti-symmetrization on the system is not enough to prevent clustering; we compute the Hall viscosity for the Halperin version of these states and the fully anti-symmetrized one and we find them being dependent on the geometry and the particle number.
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All authors Emanuele Di Salvo, Dirk Schuricht, Joost K. Slingerland, Mikael Fremling

Disordered Systems and Neural Networks

Impact of heavy-tailed synaptic strength distributions on self-sustained activity in networks of spiking neurons

Ralf Tönjes, Chunming Zheng, Wenping Cui et al. (+1 more)

We analyze states of stationary activity in randomly coupled quadratic integrate-and-fire neurons using stochastic mean-field theory. Specifically, we consider the two cases of Gaussian random coupling and Cauchy random coupling, which are representative of systems with light- or with heavy-tailed synaptic strength distributions. For both, Gaussian and Cauchy coupling, bistability between a low activity and a high activity state of self-sustained firing is possible in excitable neurons. In the system with Cauchy coupling we find analytically a directed percolation threshold, i.e., above a critical value of the synaptic strength, activity percolates through the whole network starting from a few spiking units only. The existence of the directed percolation threshold is in agreement with previous numerical results in the literature for integrate-and-fire neurons with heavy-tailed synaptic strength distribution. However, we have found that the transition can be continuous or discontinuous, depending on the excitatory-inhibitory imbalance in the network. Networks with Gaussian coupling and networks with Cauchy coupling and additional additive noise lack the percolation transition in the thermodynamic limit.
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All authors Ralf Tönjes, Chunming Zheng, Wenping Cui, Benjamin Lindner

Statistical Mechanics

Materials Beyond Hamiltonian Limits – Quantum Measurement as a Resource for Material Design

Jochen Mannhart

Recent studies have identified materials and devices whose behavior lies beyond the scope of conventional electronic-structure theory. Such theories are formulated entirely in terms of Hamiltonian evolution and therefore describe only unitary dynamics and thus only a restricted class of quantum systems. In contrast, electron systems that incorporate quantum measurement as an intrinsic dynamical element undergo Hamiltonian evolution interleaved with projection-induced state updates. This unitary-projective dynamics breaks constraints imposed by purely unitary evolution and permits stochastic population transfer between symmetry-related transport channels, thereby enabling fundamentally new material functionalities. This insight motivates the deliberate design of materials and devices that harness unitary-projective dynamics. This article explores the foundations of unitary-projective electron dynamics and charts the resulting landscape of quantum materials and their functionalities. Model calculations demonstrate passive mesoscopic structures with intrinsic nonreciprocal single-electron transmission, materials exhibiting a novel category of magnetism, and possible platforms for energy harvesting and conversion with efficiencies that exceed the standard Carnot limit.
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Statistical Mechanics

Strict Entropy Decrease of Clausius Entropy in an Isolated System with Energy-Form Conversion: Theoretical Proof, Numerical Illustration, and Critical Examination

Ting Peng

This paper is accountable only to explicitly stated physical assumptions and strict logical inference. Its goal is to run a rigorous stress test of second-law claims within the Clausius framework. We work directly with Clausius's entropy definition for an isolated composite with energy-form conversion. Heat is withdrawn from a cold releasing subsystem with relatively small heat capacity, converted to electrical energy, and then delivered as heat to a hotter subsystem. In the ideal limit, the electrical leg contributes negligibly to Clausius entropy accounting, so the modeled reservoir Clausius sum is \[ \Delta S_{\mathrm{Cl}} = Q\!\left(\frac{1}{T_B}-\frac{1}{T_A}\right) < 0. \] The paper provides a derivation, numerical illustrations, and a scope analysis; any claimed contradiction should be interpreted as a compatibility issue between different axiom sets, not as an algebraic error in the Clausius bookkeeping above.
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Materials Science

Electric toroidal octupolar symmetry in pyrite FeS$_2$ probed by Raman optical activity

Yuki Suganuma, Gakuto Kusuno, Hikaru Watanabe et al. (+4 more)

We report Raman optical activity in pyrite FeS$_2$, which hosts an electric toroidal octupolar symmetry. A clear and reproducible sign reversal of the circular intensity difference is observed between neighboring $\{111\}$ faces under cross-circular polarization. The signal appears only for the doubly degenerate $E_g$ phonon mode and is absent for other modes, consistent with symmetry analysis. First-principles calculations reproduce these features, establishing Raman optical activity as a probe of higher-rank axial multipolar symmetry.
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All authors Yuki Suganuma, Gakuto Kusuno, Hikaru Watanabe, Rikuto Oiwa, Hitoshi Mori, Ryotaro Arita, Takuya Satoh

Mesoscale and Nanoscale Physics

Antiferromagnetic Pure Spin Current Memdevices

Martin Latorre, Gaspar De la Barrera, Roberto E. Troncoso et al. (+1 more)

Spin currents can be generated through various mechanisms, including the piezospintronic effect, which arises when strain or lattice distortions induce a change in the dipolar spin moment, causing a pure spin current without necessarily being accompanied by net charge transport. This opens new possibilities for low-power information processing and novel device architectures. In this work, we propose a novel effect, the spintronic-magneto-impedictive effect, as the theoretical basis for a pure spin-current memory-like device based on antiferromagnetic components. We focus on materials that can be modeled by the so-called spin-Rice-Mele Hamiltonian, incorporating a magnetic field gradient that explicitly breaks inversion symmetry. Our results shed light on how spin currents are generated and controlled, providing new insights into the potential of these materials for next-generation spintronic technologies.
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All authors Martin Latorre, Gaspar De la Barrera, Roberto E. Troncoso, Alvaro S. Nunez

Mesoscale and Nanoscale Physics

A closed-loop platform for the design and nanoscale imaging of GHz acoustic metamaterials

Federico Maccagno, Jasleen Kaur, Benjamin H. November et al. (+5 more)

Band structure engineering in surface acoustic wave (SAW) metamaterials could advance both classical telecommunications and quantum information processing. However, no imaging technique has demonstrated the necessary capability to resolve sub-$\mu$m traveling SAWs across wide GHz bandwidths. Existing methods capture only fragments of the dispersion at discrete frequencies, preventing systematic characterization and control of SAW-based metamaterials. Here, we develop electrostatic force microscopy (EFM) to enable real-space imaging of traveling SAWs in honeycomb metamaterials on LiNbO$_3$. Our application leverages sub-200 nm spatial resolution, broad GHz bandwidth, and non-contact imaging to map complex band structures with continuous frequency resolution and expanded frequency range, while preserving sub-lattice detail. Using EFM, we map the full relevant frequency range around the Dirac point of a SAW graphene analog, including the acoustic Dirac cones, and the transition from ballistic to diffusive SAW transport regime. Furthermore, by breaking sublattice symmetry, we tune the opening of a band gap at the Dirac point, and image frequency-dependent wave localization on sublattice sites. Our EFM technique closes the loop between design and real-space validation, streamlining the engineering of arbitrary SAW landscapes for next-generation applications spanning telecommunications, microfluidics, and quantum acoustics.
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All authors Federico Maccagno, Jasleen Kaur, Benjamin H. November, Layan Ansari, Daria-Teodora Harabor, Rares-Georgian Mihalcea, Harris Pirie, Jennifer E. Hoffman

Soft Condensed Matter

Thermodynamics of hard-sphere fluids in polydisperse random porous media: Extended scaled particle theory

T. Hvozd, M. Hvozd and M. Holovko

Accurate descriptions of reference systems are a central task in liquid-state theories for the study of more complex systems. Using scaled particle theory (SPT), we derive a fully analytical description of the thermodynamic properties of a hard-sphere (HS) fluid confined in size-polydisperse HS random porous media, extending the existing approaches to higher matrix packing fractions. We calculate chemical potentials for a wide range of porous-matrix parameters, including the matrix packing fraction, degree of polydispersity, and particle-size distributions. Within the proposed framework, our results show excellent agreement with available Monte Carlo simulations and previous integral-equation theories over a broad range of matrix packing fractions, $0.1 \leqslant \eta_0 \leqslant 0.3$, and degrees of polydispersity.
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Materials Science

Exploring self-driving labs for optoelectronic materials

Jonathan Staaf Scragg

Self-driving laboratories (SDLs), by combining automation with machine learning-guided experiment selection, have the potential to transform experimental materials science. To date, most SDLs have been optimisation-driven, designed to rapidly converge on performance metrics, by embedding multiple mechanistic layers within platform-specific surrogate models. Such approaches excel at process tuning yet offer limited insight into the underlying physics governing synthesis-property relationships. Here we articulate a complementary paradigm: the exploration-driven, or scientific, SDL, whose primary purpose is the generation of data for data-driven science. We exemplify this concept for the case of inorganic optoelectronic materials, arguing that defect physics, which forms the central mechanistic link between synthesis conditions and functional properties, provides the foundation for designing a suitable SDL. Because defect populations and their spatial organisation cannot generally be resolved directly - nor fully predicted from first principles - the task of the SDL is to generate datasets in which thermodynamic and kinetic synthesis variables are systematically perturbed and defect-sensitive observables measured in parallel. From this basis, we propose a set of design principles for scientific SDLs that will enable them to operate close to the physics of optoelectronic materials, thereby generating transferrable and reusable datasets offering radical insight. We use Cu2ZnSn(S,Se)4 as a case study, both to show the scale of the task of defect-aware materials exploration as well to highlight as the deficiencies in the current paradigm. We propose that properly designed SDLs can generate the structured datasets necessary to enable mechanistic inference and advance synthesis-aware materials design.
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Materials Science

SAM Molecular Stacking with Heterogeneous Orientationfor High-Performance Perovskite Photovoltaics

Lei Huang, Kai-Li Wang, Zhang Chen et al. (+11 more)

This study demonstrates that thermal-evaporated SAM (eSAM) films, particularly in a thick configuration, spontaneously adopt a heterogeneous molecular orientation, forming a vertical-to-horizontal gradient in molecular packing. This unique architecture establishes a graded energy barrier, which is shown to facilitate more efficient hole transport compared with the single energy barrier presented by conventional thin SAMs. In conclusion, while solution-processed SAMs present formidable scalability challenges, the thermal evaporation of SAMs offers a viable pathway toward industrial-scale fabrication. The strategy of employing thick eSAM films with gradient molecular packing not only circumvents the uniformity issues of solution methods but also introduces a superior structure for charge transport, positioning it as a promising enabler for the commercialization of high-efficiency perovskite photovoltaics. The inability to achieve uniform hole transport with solution-processed self-assembled monolayers (SAMs) constitutes a fundamental bottleneck for scaling perovskite photovoltaics. Herein, we demonstrate that thermal-evaporated SAMs (eSAMs) overcome this limitation by enabling precise thickness control. Crucially, a thickened eSAM spontaneously forms a vertical-to-horizontal gradient in molecular orientation, which creates a descending energy barrier that directionally facilitates hole transport. This tailored interface also ensures excellent surface coverage and directs the growth of high-quality perovskite films. Consequently, the resultant photovoltaic devices set new benchmarks, delivering impressive power conversion efficiencies (PCEs) of 21.46% (small-area, 0.108 cm2) and 19.38% (large-area module, 15.52 cm2) for fully vacuum-evaporated devices, while also setting an impressive PCE of 23.67% for eSAM-based devices with solution-processed perovskites.
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All authors Lei Huang, Kai-Li Wang, Zhang Chen, Zhen-Huang, Saidjafar Murodzoda, Xin Chen, Jing Chen, Chun-Hao Chen, Yu Xia, Yu-Tong Yang, Jia-Cheng Li, Dilshod Nematov, Ilhan Yavuz, Zhao-Kui Wang

Materials Science

Ideal band structures for high-performance thermoelectric materials with band convergence

Yuya Hattori, Hidetomo Usui and Yoshikazu Mizuguchi

We investigate optimal band structures in band-converged systems to achieve high zT using numerical calculations based on a virtual spectral conductivity model. We consider a two parabolic band system, in which multiple band parameters can be independently controlled. Despite its simplicity, this model provides theoretical validation of empirical trends observed in thermoelectric materials. Our results provide a physically transparent set of design principles for band-structure engineering, offering quantitative design guidelines for the development of a wide range of thermoelectric materials. The main conclusions are as follows: (i) When a band does not cross the chemical potential and |{\mu}-E_edge |>5k_B T, the contribution of the band to zT is negligibly small; (ii) To suppress the bipolar effect, a band gap E_g satisfying E_g>5k_B T_op, where T_op is the operating temperature, is required; (iii) In band-converged systems, the energy separation between the band edge {\Delta}E should satisfy {\Delta}E~0 to maximize zT when interband scattering is insignificant; (iv) Achieving high spectral conductivity {\Sigma} (high band degeneracy N, density of states effective mass m_DOS^*, and relaxation time {\tau}) near the band edge is essential for achieving high zT.
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Strongly Correlated Electrons

Unveiling the magnetic ground states in the iridate double perovskite Pr(2-x)SrxMgIrO6 (x = 0 and 0.5) series

Abhisek Bandyopadhyay, Debu Das, Dheeraj Kumar Pandey et al. (+3 more)

We report here the results of a detailed magnetic, thermodynamic, and neutron powder diffraction (NPD) studies carried out on the double perovskite iridates Pr(2-x)SrxMgIrO6 (x = 0 and 0.5). Temperature dependent bulk DC susceptibility data clearly reveals a sharp antiferromagnetic (AFM) transition at 14.5 K in Pr2MgIrO6(x = 0). Next, a weaker signature of an AFM transition at a lower temperature (6 K) is observed in x = 0.5 i.e., Pr1.5Sr0.5MgIrO6 (PSMIO1505). The observed magnetic transitions are further corroborated by the presence of anomalies around the same temperatures in our T-dependent specific heat results. The charge states of both Pr and Ir cations have been confirmed to be the expected ones (3+ for Pr in both the compounds, while Ir is in a pure 4+ state for x = 0 and in a mixed 4+/5+ state for x = 0.5) from the core-level x-ray photoemission spectroscopy (XPS) measurements. Using neutron powder diffraction (NPD) the magnetic ground states and the magnetic moment values were determined for both compounds. Both the Pr- and Ir-sites undergo AFM ordering below the respective transition temperatures, designated by the propagation vector k = ( 1/2 , 0, 1/2 ), in both the compounds.
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All authors Abhisek Bandyopadhyay, Debu Das, Dheeraj Kumar Pandey, C. Ritter, D. T. Adroja, Sugata Ray

Materials Science

Improved cycling stability and lithium utilization in trilayer Al-LLZO revealed by Electrochemical cycling performance

Naisargi Kanabar, Seiichiro Higashiya and Haralabos Efstathiadis

Garnet-type Li$_{6.25}$Al$_{0.25}$La$_3$Zr$_2$O$_{12}$ (Al-LLZO) solid electrolytes are promising for all-solid-state batteries but are limited by interfacial resistance. In this work, dense and graded tri-layer Al-LLZO electrolytes were fabricated and tested in Li/Al-LLZO/NMC(111) full cells. After 25 cycles, the tri-layer cell delivered discharge capacity of $\sim$55 mAhg$^{-1}$, nearly twice that of the dense Al-LLZO ($\sim$27 mAhg$^{-1}$). EIS showed lower initial interfacial resistance ($\sim$373 $\Omega$) and improved stability. SEM confirmed a porous-dense-porous structure, while NRA revealed enhanced near-surface lithium ($\sim$75%) compared to dense Al-LLZO ($\sim$48%). These results highlight the role of microstructural grading in improving lithium distribution and cell performance.
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Statistical Mechanics · Cross-listed from quant-ph

Resonance-Suppression Principle for Prethermalization beyond Periodic Driving

Jian Xian Sim

Non-equilibrium dynamics of strongly and rapidly driven quantum many-body systems is poorly understood beyond periodic driving, where heating is exponentially slow in the drive frequency (Floquet Prethermalization). In contrast, non-periodic drives were found to exhibit widely different heating scalings with no unifying principle. This work identifies a resonance-suppression principle governing slow heating up to a prethermal lifetime $\tau_*$: When the drive's spectral arithmetic structure restricts multiphoton resonances, $\tau_*$ is controlled by low-frequency spectral suppression. The principle distinguishes (i) Single-photon suppression, quantified by a low-frequency suppression law $f(\Omega)$ for the drive's Fourier Transform weight near $\Omega=0$, from (ii) Multi-photon suppression, where nested commutators remain controlled if exceptional arithmetic structure satisfies a subadditive property. Remarkably, if multi-photon suppression holds, $\tau_*$ scaling with drive speed $\lambda$ is governed by $f(\Omega)$. This law of $\tau_*$ is found through a small-divisor mechanism in this work's iterative rotating frame scheme. Multi-photon suppression breakdown separates $\lambda$-scaling of $\tau_*$ in linear response and non-perturbative theory, shown by a case study of Quasi-Floquet driving. The principle is applied to (i) Resolve inconsistencies in literature on non-periodic driving, and (ii) Provide design principles for engineering prethermal phases of matter in programmable quantum simulators, exemplified by new non-periodic `Factorial' drives with tunable $\tau_*$.
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Strongly Correlated Electrons

Dynamical spin correlations in kagome antiferromagnets: comparison of Abrikosov fermion and Schwinger boson approaches beyond mean field

Daiki Sasamoto and Joji Nasu

Quantum spin liquids exhibit fractionalized spin excitations as a consequence of strong quantum many-body effects. The kagome antiferromagnetic Heisenberg model is a promising candidate for a quantum spin-liquid ground state; however, the nature of its excitation spectrum remains controversial, particularly regarding the presence of a spin gap and the gauge structure coupled to fractional quasiparticles. To address these issues, parton approaches have been extensively employed, where spin operators are represented in terms of fermionic or bosonic quasiparticles within the Abrikosov fermion and Schwinger boson frameworks. Thus far, these approaches have been pursued independently, and it has remained unclear how the results obtained from these frameworks compare, particularly with respect to the spin dynamics and gauge structure of the kagome antiferromagnet. Here, we investigate the dynamical spin structure factor of the antiferromagnetic Heisenberg model with a Dzyaloshinskii-Moriya interaction on the kagome lattice, relevant to herbertsmithite, by employing both approaches. We find that the dynamical spin structure factor obtained from the Abrikosov fermion mean-field theory exhibits dome-shaped features, and that its continuum structure significantly depends on the gauge structure of the spin-liquid ansatz. On the other hand, the Schwinger boson mean-field theory yields a concave-down structure in the low-energy region, distinct from that obtained using the Abrikosov fermion approach. Moreover, incorporating many-body effects beyond the mean-field approximation substantially reduces the low-energy gap and enhances the low-energy spectral weight, consistent with experimental observations. Our results suggest the importance of many-body effects in the Schwinger boson theory for capturing the low-energy spin dynamics of kagome antiferromagnets.
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Materials Science · Cross-listed from physics.optics

Freeform Spectrally Stable Topological Photonic Vortex Resonators

Yuma Kawaguchi, Daria Smirnova, Filipp Komissarenko et al. (+6 more)

Topological concepts have been at the forefront of materials research in recent years, driving a revolution in our understanding of the response of quantum materials and enabling new ways to manipulate light and sound in topological metamaterials. Topological defects and topological boundaries of different dimensions have driven a paradigm shift in photonics, where topological photonic crystals and metamaterials can be engineered to create one-way flow of energy robust to defects or to control such flows with synthetic degrees of freedom along topological domain walls. More recently, topological point singularities encoded into photonic structures have been shown to enable confinement of optical modes with the topologically nontrivial nature of the cavity imprinted into the vorticity of optical far fields. Here we demonstrate that the two latter concepts - domain wall and point singularities - can be unified into an even more powerful tool to enable arbitrarily shaped resonant cavities of any dimension supporting spectrally stable zero-energy modes. We experimentally confirm that such modes, whose existence is guaranteed by topological principles, allow an unprecedented degree of control over the optical field, which appears to have no phase modulation across space, can have any desirable radiation pattern, and enables spectral stability regardless of shape or length.
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All authors Yuma Kawaguchi, Daria Smirnova, Filipp Komissarenko, Daria Kafeeva, Svetlana Kiriushechkina, Jeffery Allen, Monica Allen, Andrea Alù, Alexander Khanikaev

Quantum Gases

Critical dynamics of the superfluid phase transition in Model F

Chandrodoy Chattopadhyay, Robert Maguire, Josh Ott et al. (+2 more)

We describe numerical simulations of the critical dynamics near the superfluid phase transition. The calculations are based on an implementation of a stochastic hydrodynamic theory known as model F in the classification of Hohenberg and Halperin. This theory is expected to describe dynamic scaling near the lambda transition in liquid $^4$He, Bose-Einstein condensation in ultracold atomic gases, and the superfluid transition in the unitary Fermi gas. Our simulation is based on a Metropolis algorithm previously applied to the critical endpoint of the liquid-gas phase transition in ordinary fluids. In the model E truncation of model F we obtain the expected dynamical exponent $z\simeq 3/2$. We observe the emergence of a propagating second sound mode at the phase transition. The second sound diffusivity $D_s$ is consistent with the scaling relation $D_s\sim \xi^{x_\kappa}$, where $\xi$ is the correlation length and $x_\kappa=1/2$.
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All authors Chandrodoy Chattopadhyay, Robert Maguire, Josh Ott, Thomas Schaefer, Vladimir V. Skokov

Strongly Correlated Electrons

Control of band structure in the altermagnetic candidate MnTe by temperature and strain

Shin-ichi Kimura, Hironao Suwa, Kangle Yuan et al. (+4 more)

The temperature and strain dependences of the optical conductivity spectrum of hexagonal manganese telluride (MnTe) were measured, revealing absorption in the terahertz (THz) region from spin-split bands to acceptor levels. The temperature dependence of the THz absorption peak is consistent with that of a ferromagnetic phase transition, even though MnTe exhibits no net magnetism. The temperature dependence was attributed to a change in the altermagnetic electronic structure. Under negative uniaxial strain, the THz peak shifts to the high-energy side, suggesting spin-splitting bands at energies away from EF, consistent with the theoretical prediction that the spin-splitting angle decreases. The observed behavior of the THz peak clearly shows that MnTe has the altermagnetic electronic structure. Additionally, a Fano-like asymmetric line shape in the optical phonon absorption was observed, possibly originating from interactions with the alternative spin-split bands.
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All authors Shin-ichi Kimura, Hironao Suwa, Kangle Yuan, Hiroshi Watanabe, Takuto Nakamura, Haan Kyul Yun, Myung-Hwa Jung

Sunday 22 March

Statistical Mechanics

Breakdown of Perturbative Expansions and Exact Algebraic Absorption of Finite-Size Fluctuations in Statistical Mechanics

Hiroki Suyari

In statistical mechanics, evaluating finite-size macroscopic fluctuations typically relies on Edgeworth expansions. However, these perturbative methods append additive polynomial corrections that break down in the large deviation regime, yielding unphysical negative probabilities. We propose a structural resolution: rather than relying on additive polynomials, we absorb finite-size skewness using a globally stable $q$-deformed framework. By introducing a dynamic scaling law $1-q_n = O(n^{-1})$ for the nonextensivity parameter, we prove this $q$-deformed framework captures macroscopic higher-order fluctuations in independent and identically distributed (i.i.d.) systems. Specifically, this algebraic tuning absorbs third-order skewness while guaranteeing probability density nonnegativity across the entire domain. Furthermore, the $k$-th degree term of this $q$-logarithmic expansion corresponds to the $O(n^{1-k/2})$ asymptotic order of classical $(k+1)$-th moment Edgeworth corrections. This correspondence functions as a stable resummation of divergent asymptotic expansions, establishing a mathematical bridge between finite-size i.i.d. fluctuations and the Tsallis statistics governing complex systems.
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Statistical Mechanics · Cross-listed from cs.AI

Intelligence Inertia: Physical Isomorphism and Applications

Jipeng Han

Classical frameworks like Fisher Information approximate the cost of neural adaptation only in low-density regimes, failing to explain the explosive computational overhead incurred during deep structural reconfiguration. To address this, we introduce Intelligence Inertia, a property derived from the fundamental non-commutativity between rules and states ($[\hat{S}, \hat{R}] = i\mathcal{D}$). Rather than claiming a new fundamental physical law, we establish a heuristic mathematical isomorphism between deep learning dynamics and Minkowski spacetime. Acting as an effective theory for high-dimensional tensor evolution, we derive a non-linear cost formula mirroring the Lorentz factor, predicting a relativistic $J$-shaped inflation curve – a computational wall where classical approximations fail. We validate this framework via three experiments: (1) adjudicating the $J$-curve divergence under high-entropy noise, (2) mapping the optimal geodesic for architecture evolution, and (3) deploying an inertia-aware scheduler wrapper that prevents catastrophic forgetting. Adopting this isomorphism yields an exact quantitative metric for structural resistance, advancing the stability and efficiency of intelligent agents.
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Materials Science

Inverse design of heterodeformations for strain soliton networks in bilayer 2D materials

Md Tusher Ahmed and Nikhil Chandra Admal

Strain soliton networks strongly influence the structural and electronic properties of heterodeformed bilayer systems, yet their design remains challenging due to the high dimensionality of heterodeformation space and the absence of a direct map between deformation and network geometry. In this work, we introduce a geometric framework that establishes a one-to-one mapping between heterodeformations and the geometry of the strain soliton network expressed as line vector-Burgers vector pairs. The admissible networks are constrained by topology dictated by the generalized stacking fault energy landscape. We show that the moiré Bravais lattice, corresponding to a uniform heterodeformation, alone is insufficient to characterize the interface: distinct heterodeformations can share identical moiré Bravais lattices while producing different soliton networks, reflecting an inherent many-to-one mapping when only translational symmetry is considered. In contrast, the soliton network encodes the full multilattice geometry of the interface, including topology and connectivity, which are not captured by the moiré Bravais lattice alone. The proposed framework enables the direct construction of heterodeformations from target networks, providing a systematic route for inverse design of moiré interfaces beyond conventional twist-based approaches.
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Strongly Correlated Electrons

Colossal Terahertz Magnetoresistance from Magnetic Polarons in EuZn$_2$P$_2$

E. Marulanda, M. Dutra, N. M. Kawahala et al. (+5 more)

Magnetic polarons can generate colossal magnetoresistance in magnetic semiconductors, yet their terahertz electrodynamics remain largely unexplored. Here we report magneto-terahertz spectroscopy of the Eu-based Zintl antiferromagnet EuZn$_2$P$_2$. The low-frequency conductivity shows pronounced non-Drude behavior consistent with an evolution from isolated to overlapping magnetic polarons upon cooling. The polaron relaxation time reaches a maximum near the Néel temperature at zero field and exhibits a strong magnetic-field dependence. This polaron-driven reshaping of the conductivity leads to a strongly frequency-dependent magnetoresistance that becomes colossal in the terahertz range, reaching about 90~% at 1.5~THz, roughly three times larger than the zero-frequency limit value. These results demonstrate that magnetic polarons strongly govern the low-energy electrodynamics and highlight the sensitivity of terahertz spectroscopy to polaronic magnetotransport in correlated magnetic semiconductors.
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All authors E. Marulanda, M. Dutra, N. M. Kawahala, E. D. Stefanato, G. G. Vasques, J. Munevar, M. A. Avila, F. G. G. Hernandez

Materials Science · Cross-listed from quant-ph

Enhanced Emission from Boron-Vacancy Center in Rhombohedral Boron Nitride

Nasrin Estaji, Ismaeil Abdolhosseini Sarsari, Gergő Thiering et al. (+1 more)

Boron nitride is a layered crystal whose properties depend on how its atomic sheets are stacked. Its negatively charged boron vacancy is a well-established magnetic defect that can be prepared and read out optically, but in the common hexagonal form it emits very little light, because the symmetry of the surrounding lattice forbids the relevant optical transition. Here we show, using first-principles calculations, that stacking the sheets in the rhombohedral sequence instead removes this restriction and increases the emitted intensity by one to two orders of magnitude, while the magnetic properties remain comparable or improve. We predict that the resulting emission is bright enough for a single defect to be addressed at room temperature, and that a sharp emission line, absent in the hexagonal form, should appear on cooling. Stacking order therefore acts as a design parameter for tailoring the quantum properties of defects embedded in layered materials.
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All authors Nasrin Estaji, Ismaeil Abdolhosseini Sarsari, Gergő Thiering, Adam Gali

Superconductivity

Hopping mechanism for superconductivity revealed by Density Functional Theory

Jose A. Alarco and Ian D. R. Mackinnon

Electronic band structures of MgB2 show that sigma bands along the G-A reciprocal direction (parallel to the c-axis) in combination with electron-phonon coupling to the E2g mode effect charge transfer. DFT calculation shows that the cosine-shaped sigma band along G-A reveals energy asymmetry matching the superconducting gap. Sigma bands parallel to the G-A direction calculated at intervals along the G-M direction show band structure unlike that at high symmetry nodes. For example, bands in close proximity to EF do not emulate the degeneracy of bands along G-A. Near EF, bands split and align favourably for electron-hole pairing with the nodal inflection point located at EF. With increased isotropic pressure, changes to sigma bands near EF occur with increased intersections of folded Fermi-surfaces and band crossings. Band intersections that define the fraction of coherent nesting at pressure show equivalent estimates for Tc determined by experiment and by the Kohn phonon anomaly. Tight-binding equations, including corrections to describe the observed asymmetry of a cosine-shaped band, show that a hopping mechanism is associated with cosine band asymmetry, the superconducting gap and Fermi surface nesting. Cosine band asymmetry may be inimical to superconductivity mechanisms in multi-element compounds.
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